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NASA NTRS2020

Impact of Bias in the Marine Air Temperature Observation Set on Atmospheric Reanalyses

Marine air temperature observations are collected by volunteer observing ships carrying automatic meteorological sensor packages. Close proximity of the package mount to a dark colored ship's deck is known to introduce a warm bias on sunny afternoons in summer under low wind conditions. This observation set is used as an influential constraint in the MERRA-2 reanalysis, as well as several other reanalyses, in the poorly sampled surface marine boundary layer. Here we explore the consequences of bias in the marine air temperature observation set during the 36 year period 1980-2015. Marine air temperature observations have mainly been collected along major shipping routes, with the densest coverage in the North Atlantic and North Pacific. In the first part of this presentation we review the historical observation coverage and compare air temperature and contemporaneous SST measurements to identify systematic differences. The comparison suggests the presence of diurnal bias in the air temperature observations peaking in subtropics and midlatitudes latitudes in mid-afternoon local time. In the second part we explore the impact of the marine air temperature observations on MERRA-2 through analysis of the terms in the temperature forecast tendency equation, the equation which describes the contributions to changes in temperature during each analysis cycle. Examination of the temperature forecast tendency equation allows us to separate systematic errors due to such processes and radiation, mixing, and advection and allows us to identify the major source of systematic forecast tendencies. The results show that the marine air temperature measurements introduce an error that can reach 0.4K/dy which also peaks in local afternoon at subtropical latitudes. This bias varies with season and has gradually reduced from the beginning of the MERRA-2 reanalysis in 1980. In the final part we conduct numerical experiments with a version of the MERRA-2 analysis system, comparing experiments when the marine air temperature observations are included or withheld from the analysis system.

Akella, Santharam↗
NASA NTRS2020

Influence of Sea-Ice Anomalies on Antarctic Precipitation Using Source Attribution in the Community Earth System Model

We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and source–receptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50∘ S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr−1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr−1). The contrast in contribution from the Southern Ocean, 102 Gt yr−1, is even more significant compared to the interannual variability of 35 Gt yr−1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SIC–SST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer.

Wang, Hailong↗
NASA NTRS2020

Designing an Optimal Ensemble Strategy for GMAO S2S Forecast System

GMAO Sub/Seasonal prediction system (S2S) is being readied for a major upgrade to GEOS-S2S Version 3. An important factor in successful extended range forecast is the definition of an ensemble For initialization of the ensemble we propose a combination of lagged and burst initial conditions. We plan to run a relatively large ensemble of 40 members for sub-seasonal forecast (up to 3 months), at which point we sub-sample the ensemble, and continue the forecast with 10 members (up to 12 months). Here we present the results of the extensive testing of various ways to generate the perturbations to the initial conditions and the validation of the stratified sampling strategy we chose.To generate perturbations for the burst ensemble members we used scaled differences of pairs of analysis states separated by 1-10 days, randomly chosen from a corresponding season. We considered perturbing separately only the atmospheric fields or only the ocean or both of the forecast initial conditions. Considering varying separation times between the analysis states, we were able to produce perturbations sampling various modes of variability. Focusing on the ENSO SST indices, we found that all types of perturbations are important for the ensemble spread.Our ensemble size for sub-seasonal forecasts was determined as to maximize the skill of predicting some of the leading modes of boreal winter atmospheric modes, NAO, PNA and AO. It is not feasible to run equally large ensemble for seasonal forecasts. Using a stratified sampling procedure we can identify the emerging directions of error growth. By comparing the stratified ensemble with randomly sampled ensemble of the same size, we were able to show that the former better estimates the mean of the original large ensemble.

Borovikov, Anna↗
NASA NTRS2019

FUN3D and USM3D Analysis of the Propulsion Aerodynamic Workshop 2018 S-Duct Test Case

This work presents the results of Fun3D and USM3D analyses that were performed for the 4th AIAA Propulsion Aerodynamics Workshop (PAW). The PAW workshop is separated into three sections that focus on internal duct flows, nozzle flows and a special topic. This paper focuses on the internal duct flow section of PAW04 while an accompanying paper discusses the analyses performed for the nozzle portion. For the internal duct flow section, the PAW04 participants were provided with the two configurations consisting of an S-duct with and without aerodynamic interface plane (AIP) rake legs modeled. The participants were asked to perform a grid refinement study as well as a turbulence model study for the configuration with the rake legs. The analyses discussed here were performed on custom grids developed under the guidelines of the workshop. Additionally, the paper discusses the development and use of flow controllers for matching the desired flow characteristics. The results show that both solvers do well for predicting internal flow characteristics of the S-duct based on direct comparison with the experimental data. However, the CFD-to-CFD comparison proved to be more challenging due to the localized occurrence of supersonic flow near the rake legs when using the mass flow controller. A turbulence model study was performed to compare the two-equation SST model to the SA-QCR model. The results show that although the turbulence model does affect the solution, it makes a minimal impact on pressure recovery and inlet distortion intensity for this case. Suggestions for future workshops include gridding guidelines similar to those employed for the Drag Prediction Workshop series for the grid refinement study and a time accuracy study.

Carter, Melissa B.↗
NASA NTRSDate not supplied

NASA Small Spacecraft Technology Program (SSTP) Overview, Recent Technology Demonstrations, and Upcoming SSTP Demonstrations

The Small Spacecraft Technology Program (SSTP) within the NASA Space Technology Mission Directorate (STMD) is chartered to enable mission capabilities that are more rapid, more transformative, and more affordable than previously achievable. To that end, the SST program seeks to: • Enable the execution of missions at much lower cost than previously possible. • Substantially reduce the time required for development of spacecraft, from authority to proceed until initial launch capability. • Enable and demonstrate new mission architectures that small spacecraft are uniquely suited for. • Expand the capability of small spacecraft to execute missions at new destinations and in challenging new environments. • Enable the augmentation of existing assets and future missions with supporting small spacecraft. This paper will describe the NASA SSTP SmallSat Technology Partnerships (STP), completed and upcoming Missions Capability Demonstrations for technology demonstrations under SSTP1 and provides a synopsis of the leveraged investments under the Small Business Innovation Research (SBIR) Program and Small Business Technology Transfer (STTR). A brief overview of the Small Spacecraft Systems Virtual Institute (S3VI) and its current activities performed in conjunction with SSTP is also provided.

Roger C. Hunter↗
NASA NTRS2020

The Role of Oceanic Processes in the Initiation of Boreal Winter Intraseasonal Oscillations Over the Indian Ocean

Observational analyses and ocean general circulation model experiments were performed to understand the influence of oceanic processes on warm sea surface temperature anomalies (SSTAs) prior to convection initiation of boreal winter intraseasonal oscillations (ISOs), including the Madden‐Julian Oscillation (MJO), in the tropical Indian Ocean. We found 39 strong ISOs that passed over the Indian Ocean Warm Pool (WP) region during the November–April season of the 2001–2012 period. Seventeen of them (44%) initiated over the Seychelles‐Chagos Thermocline Ridge (SCTR) before propagating eastward to the WP and Maritime Continent. Including only global‐scale MJOs, 71% (24%) of the remaining MJO events initiated from the SCTR (WP). Four (seven) SCTR (WP) ISO events were preceded by SSTAs that were strongly influenced by wind stress‐driven oceanic processes; all four (2/7) SCTR (WP) events were MJOs. Composite analyses of the four oceanic process influenced SCTR MJO events showed that wind stress‐driven oceanic processes contributed about 30% (between 0.1 and 0.2 °C) of the preconvection warming in the SCTR, which coincides with the Intertropical Convergence Zone with mean SST > 28 °C. Reduced upwelling and entrainment played a more important role than horizontal advection in elevating the +SSTAs. Case studies revealed that the two ocean process‐influenced primary MJO SCTR events were also associated with oceanic equatorial Rossby waves. Furthermore, results of a linear atmospheric mixed layer model indicated that boundary layer processes related to SSTAs contributed approximately half of the total convergence during MJO initiation, relative to the effect of the free troposphere, for the Rossby wave‐influenced events.

MJO Initiation↗
NASA NTRS2020

GISS Model E2.2: A Climate Model Optimized for the Middle Atmosphere. Part 2: Validation of Large-Scale Transport and Evaluation of Climate Response

Here we examine the large‐scale transport characteristics of the new ``Middle Atmosphere" NASA Goddard Institute for Space Studies climate model (E2.2). First we evaluate the stratospheric transport circulation in historical atmosphere‐only simulations integrated with interactive trace gas and aerosol chemistry. Compared to lower vertical resolution model versions, E2.2 exhibits improved tropical ascent and older stratospheric mean ages that are more consistent with observed values. In the troposphere, poleward transport to the Arctic and interhemispheric mean ages in E2.2 are comparable to models participating in the Chemistry Climate Modeling Initiative. In addition to validating E2.2 we also assess its ``transport sensitivity" using the coupled atmosphere‐ocean abrupt 4xCO2 and transient 1%CO2 simulations submitted to the Coupled Model Intercomparison Project, Phase 6, along with a 2xCO2 simulation used to evaluate the linearity of the transport circulation's response to increased CO2. We show that decreases (increases) in a stratospheric mean age (idealized surface loss) tracer scale linearly with increased lower stratospheric upwelling, which also increases linearly with warming tropical sea surface temperatures (SSTs). Abrupt 2xCO2 and 4xCO2 experiments constrained with (fixed) pre‐industrial SSTs are also used to quantify the relative importance of rapid adjustments versus SST feedbacks to the transport circulation responses in the model. Finally, sensitivity experiments are presented to illustrate the impact of changes in the convective parameterization on stratospheric transport.

GISS Model E2.2↗
NASA NTRS2020

TechPort Abstracts

Collection of technology development project abstracts for STMD's technology development projects in NASA Innovative and Advanced Concepts (NIAC), Game-Changing Development (GCD), Small Spacecraft Technologies (SST) and Flight Opportunities (FO) programs.

Nathaniel James Booth↗
NASA NTRS2020

Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective56equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climatecsensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The dataset of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We don’t find a conclusive result for how cloud clustering changes as the climate warms.

Allison A. Wing↗
NASA NTRS2020

The role of blocking circulation and emerging open water feedbacks on Greenland cold‐season air temperature variability over the last century

Substantial marine, terrestrial, and atmospheric changes have occurred over the Greenland region during the last century. Several studies have documented record‐levels of Greenland Ice Sheet (GrIS) summer melt extent during the 2000s and 2010s, but relatively little work has been carried out to assess regional climatic changes in other seasons. Here, we focus on the less studied cold‐season (i.e., autumn and winter) climate, tracing the long‐term (1873–2013) variability of Greenland's air temperatures through analyses of coastal observations and model‐derived outlet glacier series and their linkages with North Atlantic sea ice, sea surface temperature (SST), and atmospheric circulation indices. Through a statistical framework, large amounts of west and south Greenland temperature variance (up to r^2~50%) can be explained by the seasonally‐contemporaneous combination of the Greenland Blocking Index (GBI) and the North Atlantic Oscillation (NAO; hereafter the combination of GBI and NAO is termed GBI). Lagged and concomitant regional sea‐ice concentration (SIC) and the Atlantic Multidecadal Oscillation (AMO) seasonal indices account for small amounts of residual air temperature variance (r^2<~10%) relative to the GBI. The correlations between GBI and cold‐season temperatures are predominantly positive and statistically‐significant through time, while regional SIC conditions emerge as a significant covariate from the mid‐20th century through the conclusion of the study period. The inclusion of the cold‐season Pacific Decadal Oscillation (PDO) in multivariate analyses bolsters the air temperature variance explained by the North Atlantic regional predictors, suggesting the remote, background climate state is important to long‐term Greenland temperature variability. These findings imply that large‐scale tropospheric circulation has a strong control on surface temperature over Greenland through dynamic and thermodynamic impacts and stress the importance of understanding the evolving two‐way linkages between the North Atlantic marine and atmospheric environment in order to more accurately predict Greenland seasonal climate variability and change through the 21st century.

air temperatures↗
NASA NTRSDate not supplied

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Favorable Pressure Gradients due to Streamline Curvature

Direct numerical simulations (DNS) of favorable-pressure-gradient turbulent boundary layers are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models. The favorable pressure gradient is induced by the streamwise curvature of the two-dimensional, planar, convex measurement surface used during experiments at the Texas A&M University. The DNS data shows good comparison with the measured velocity profiles, strain rates, and some, but not all, of the Reynolds-stress components. The discrepancies between the predicted and the measured wall-normal as well as shear stress components are primarily attributed to the lower than actual values inferred from typical PIV measurements of turbulent boundary layers. The DNS data shows a zero or slightly negative Reynolds shear stress in the outer part of the boundary-layer, which is indicative of the decaying turbulent motion under a strong favorable pressure gradient. The DNS data is also compared with the results of RANS computations based on commonly used zero, one, and two equation eddy-viscosity models. The RANS models yield reasonable comparisons with the DNS-based skin friction under zero and weak pressure gradients, but significant discrepancies under a strong pressure gradient. The k-w SST model provided the best overall predictions of skin friction, except in the region where the flow transitions from a favorable to an adverse pressure gradient. While the RANS models examined herein also give good predictions of the Reynolds shear stress under a sufficiently weak pressure gradient, none of those models are able to appropriately capture the reduction in the Reynolds stresses when the flow was subjected to a strong pressure gradient. An a priori assessment of the turbulent heat-flux prediction based on the assumption of a constant turbulent Prandtl number with the DNS data shows that while the constant turbulent Prandtl number model is effective in predicting the wall-normal component of turbulent heat flux, it does not capture the turbulent heat transfer in the streamwise direction for all the pressure gradient cases. The failure of the constant turbulent Prandtl number model highlights a requirement for more advanced models of the turbulent heat flux.

turbulent boundary layers↗
NASA NTRS2021

Southern Ocean Heat Storage, Reemergence, and Winter Sea Ice Decline Induced by Summertime Winds

The observational record shows a substantial 40-yr upward trend in summertime westerly winds over the Southern Ocean, as characterized by the southern annular mode (SAM) index. Enhanced summertime westerly winds have been linked to cold summertime sea surface temperature (SST) anomalies. Previous studies have suggested that Ekman transport or upwelling is responsible for this seasonal cooling. Here, another process is presented in which enhanced vertical mixing, driven by summertime wind anomalies, moves heat downward, cooling the sea surface and simultaneously warming the subsurface waters. The anomalously cold SSTs draw heat from the atmosphere into the ocean, leading to increased depth-integrated ocean heat content. The subsurface heat is returned to the surface mixed layer during the autumn and winter as the mixed layer deepens, leading to anomalously warm SSTs and potentially reducing sea ice cover. Observational analyses and numerical experiments support our proposed mechanism, showing that enhanced vertical mixing produces subsurface warming and cools the surface mixed layer. Nevertheless, the dominant driver of surface cooling remains uncertain; the relative importance of advective and mixing contributions to the surface cooling is model dependent. Modeling results suggest that sea ice volume is more sensitive to summertime winds than sea ice extent, implying that enhanced summertime westerly winds may lead to thinner sea ice in the following winter, if not lesser ice extent. Thus, strong summertime winds could precondition the sea ice cover for a rapid retreat in the following melt season.

Southern Ocean↗
NASA NTRS2020

Revisiting the Relationship between Atlantic Dust and Tropical Cyclone Activity using Aerosol Optical Depth Reanalyses: 2003-2018

Previous studies have noted a relationship between African dust and Atlantic tropical cyclone (TC) activity. However, due to the limitations of past dust analyses, the strength of this relationship remains uncertain. The emergence of aerosol reanalyses, including the Navy Aerosol Analysis and Prediction System (NAAPS) aerosol optical depth (AOD) reanalysis, NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and ECMWF Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA), enables an investigation of the relationship between African dust and TC activity over the tropical Atlantic and Caribbean in a consistent temporal and spatial manner for 2003–2018. Although June–July–August (JJA) 550 nm dust AOD (DAOD) from all three reanalysis products correlates significantly over the tropical Atlantic and Caribbean, the difference in DAOD magnitude between products can be as large as 60 % over the Caribbean and 20 % over the tropical North Atlantic. Based on the three individual reanalyses, we have created an aerosol multi-reanalysis consensus (MRC). The MRC presents overall better root mean square error over the tropical Atlantic and Caribbean compared to individual reanalyses when verified with ground-based AErosol RObotic NETwork (AERONET) AOD measurements. Each of the three individual reanalyses and the MRC have significant negative correlations between JJA Caribbean DAOD and seasonal Atlantic accumulated cyclone energy (ACE), while the correlation between JJA tropical North Atlantic DAOD and seasonal ACE is weaker. Possible reasons for this regional difference are provided. A composite analysis of 3 high-JJA-Caribbean-DAOD years versus 3 low-JJA-Caribbean-DAOD years reveals large differences in overall Atlantic TC activity. We also show that JJA Caribbean DAOD is significantly correlated with large-scale fields associated with variability in interannual Atlantic TC activity including zonal wind shear, mid-level moisture, and sea surface temperature (SST), as well as the El Niño–Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), implying confounding effects of these factors on the dust–TC relationship. We find that seasonal Atlantic DAOD and the AMM, the leading mode of coupled Atlantic variability, are inversely related and intertwined in the dust–TC relationship. Overall, DAOD in both the tropical Atlantic and Caribbean is negatively correlated with Atlantic hurricane frequency and intensity, with stronger correlations in the Caribbean than farther east in the tropical North Atlantic.

Dust particles↗
NASA NTRS2021

Assessment of RANS-based Transition Models based on Experimental Data of the Common Research Model with Natural Laminar Flow

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework often rely upon transition correlations that were derived from a limited number of low-speed experiments and these models often fail to account for all of the relevant transition mechanisms and/or the variation in those mechanisms with respect to changes in the significant flow parameters. Available data from a recent experiment on the Common Research Model with Natural Laminar Flow (CRM-NLF) in the National Transonic Facility at the NASA Langley Research Center are used to assess the current transition modeling capability in NASA's OVERFLOW 2.3b solver for a swept wing configuration with nonzero taper and transonic cruise conditions. Specifically, the OVERFLOW solutions are used to evaluate the accuracy and robustness of the transport-equation-based transition models. Results highlight that the Spalart-Allmaras-based amplification factor transport (AFT-2017b) equation model and Menter’s shear-stress transport equation (SST2003)-based Langtry-Menter transition models (either with or without the modeling of crossflow transition) significantly underpredict the reported extent of laminar flow region over the entire span of the wing, irrespective of which instability mechanism(s) is expected to dominate the onset of the transition process. We show that the transition correlations underlying these models fail to account for the stabilizing effect of compressibility on the Tollmien-Schlichting transition, which is likely to be a major contributor to the underprediction of the laminar flow region on the CRM-NLF. The SST-2003-based Langtry-Menter model also appears to inaccurately predict the chordwise pressure variation along the majority of the wing span at all the flow conditions studied herein, due to how the turbulence intensity levels were enforced in the computations and how that was interfering with the functioning of the underlying turbulence model within the boundary layer. The AFT and Langtry-Menter models appear to be sensitive to the level of the freestream turbulence intensity, but the degree of sensitivity varies across the models.

CFD modeling↗
NASA NTRSDate not supplied

QBO Responses to Increased CO2: The Roles of Convection and SSTs

Long-term changes to the Quasi-Biennial Oscillation (QBO) remain uncertain. Recent multimodel investigations (Richter et al. 2020a, Butchart et al. 2020) suggest that QBO amplitude will weaken in the future, but trends in QBO period and stability are unclear. Additionally, the parameterizations that generate the QBO in CMIP6 models vary greatly, and about half of CMIP6 models do not represent the QBO at all (Richter et al. 2020b). Tropical convection is likely to play a role in QBO trends, yet a majority of gravity wave parameterizations in QBO-resolving models are fixed and cannot respond to changes in convection. We consider future changes of the QBO using the NASA Goddard Institute for Space Studies (GISS) Model E2.2, which has a realistic QBO produced partly through use of a non-orographic gravity wave drag scheme that explicitly links lower stratospheric momentum fluxes to convection (Rind et al., 2014, 2020; Orbe et al. 2020). The experiments include historical integrations and abrupt increases in CO which we use to probe the roles of convection and SST feedbacks. Overall, both the QBO period and amplitude decrease in response to CO2, and our results link the period response to changes in convection and the amplitude response to changes in upwelling.

Quasi-Biennial Oscillation (QBO)↗
NASA NTRS1993

Remote Sensing of Seasonal and Annual Variation of Equatorial New Production: A Model for Global Estimates

Sea-surface temperatures (SSTs) are strongly correlated with surface nitrate concentrations in coastal upwelling regions. Upwelling also occurs in the equatorial Pacific; correlations between temperature and nitrate concentration are strong. The University of Miami weekly averaged Advanced Very High Resolution Radiometer (AVHRR) SST data for October 1986 through June 1989 have been used to compute surface nitrate concentrations from 90 deg - 180 deg W and from 15 deg S - 15 deg N. The surface areas with nitrate above detection limits are combined with existing nitrate uptake data to give weekly estimates of equatorial new production.

Barder, R.↗
NASA NTRS2014

Ocean surface carbon dioxide fugacity observed from space

We have developed and validated a statistical model to estimate the fugacity (or partial pressure) of carbon dioxide (CO2) at sea surface (pCO2sea) from space-based observations of sea surface temperature (SST), chlorophyll, and salinity. More than a quarter million in situ measurements coincident with satellite data were compiled to train and validate the model. We have produced and made accessible 9 years (2002–2010) of the pCO2sea at 0.5 degree resolutions daily over the global ocean. The results help to identify uncertainties in current JPL Carbon Monitoring System (CMS) model-based and bottom-up estimates over the ocean. The utility of the data to reveal multi-year and regional variability of the fugacity in relation to prevalent oceanic parameters is demonstrated.

Xie, Xiaosu↗